How to Index Fields for Autocompletion

1. Click Refine Your Index to configure your index.

2. In the Field Mappings section, click Add Field to open the Add Field Mapping window.

3. Click Customized Configuration.

4. Select the field to index from the Field Name dropdown.

   Note

   You can't index fields that contain the dollar ($) sign at the start of the field name.

   For field names that contain the term email or url, the Atlas Search Visual Editor recommends using a custom analyzer with the uaxUrlEmail tokenizer for indexing email addresses or URL values. Click Create urlEmailAnalyzer to create and apply the custom analyzer to the Autocomplete Properties for the field.

5. Click the Data Type dropdown and select Autocomplete.

6. (Optional) Expand and configure the Token Properties for the field. To learn more, see Configure token Field Properties.

7. Click Add.

The following is the JSON syntax for the autocomplete type. Replace the default index definition with the following. To learn more about the fields, see Field Properties.

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{
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  "mappings": {
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    "dynamic": true|false,
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    "fields": {
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      "<field-name>": {
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        "type": "autocomplete",
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        "analyzer": "<lucene-analyzer>",
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        "tokenization": "edgeGram|rightEdgeGram|nGram",
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        "minGrams": <2>,
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        "maxGrams": <15>,
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        "foldDiacritics": true|false
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      }
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    }
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  }
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}

The following index definition example uses the sample_mflix.movies collection. If you have the sample data already loaded on your cluster, you can use the Visual Editor or JSON Editor in the Atlas UI to configure the index. After you select your preferred configuration method, select the database and collection, and refine your index to add field mappings.

The following index definition example indexes only the title field as the autocomplete type to support search-as-you-type queries against that field using the autocomplete operator. The index definition also specifies the following:

• Use the standard analyzer to divide text values into terms based on word boundaries.

• Use the edgeGram tokenization strategy to index characters starting at the left side of the words .

• Index a minimum of 3 characters per indexed sequence.

• Index a maximum of 5 characters per indexed sequence.

• Include diacritic marks in the index and query text.

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{
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  "mappings": {
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    "dynamic": false,
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    "fields": {
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      "title": {
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        "type": "autocomplete",
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        "analyzer": "lucene.standard",
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        "tokenization": "edgeGram",
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        "minGrams": 3,
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        "maxGrams": 5,
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        "foldDiacritics": false
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      }
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    }
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  }
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}

The following index definition example uses the sample_mflix.movies collection. If you have the sample data already loaded on your cluster, you can use the Visual Editor or JSON Editor in the Atlas UI to configure the index. After you select your preferred configuration method, select the database and collection, and refine your index to add field mappings.

You can index a field as other types also by specifying the other types in the array. For example, the following index definition indexes the title field as the following types:

• autocomplete type to support autocompletion for queries using the autocomplete operator.

• string type to support text search using operators such text, phrase, and so on.

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{
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  "mappings": {
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    "dynamic": true|false,
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    "fields": {
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      "title": [
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        {
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          "type": "autocomplete",
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          "analyzer": "lucene.standard",
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          "tokenization": "edgeGram",
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          "minGrams": 2,
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          "maxGrams": 15,
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          "foldDiacritics": false
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        },
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        {
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          "type": "string"
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        }
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      ]
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    }
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  }
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}

The following index definition example uses the sample_mflix.users collection. If you have the sample data already loaded on your cluster, you can use the Visual Editor or JSON Editor in the Atlas UI to configure the index. After you select your preferred configuration method, select the database and collection, and refine your index to add field mappings.

The following index definition example indexes only the email field as the autocomplete type to support search-as-you-type queries against that field using the autocomplete operator. The index definition specifies the following:

• Use the keyword analyzer to accept a string or array of strings as a parameter and index them as a single term (token).

• Use the nGram tokenizer to tokenize text into chunks, or "n-grams", of given sizes.

• Index a minimum of 3 characters per indexed sequence.

• Index a maximum of 15 characters per indexed sequence.

• Include diacritic marks in the index and query text.

You can also use the uaxUrlEmail tokenizer to tokenizes URLs and email addresses. To learn more, see uaxUrlEmail.

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{
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  "mappings": {
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    "dynamic": true,
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    "fields": {
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      "email": {
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        "type": "autocomplete",
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        "analyzer": "lucene.keyword",
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        "tokenization": "nGram",
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        "minGrams": 3,
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        "maxGrams": 15,
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        "foldDiacritics": false
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      }
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    }
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  }
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}